Computational structure modeling for diverse categories of macromolecular interactions

Aderinwale, Tunde; Christoffer, Charles; Sarkar, Daipayan; Alnabati, Eman; Kihara, Daisuke

doi:10.1016/j.sbi.2020.05.017

Cited by 24 publications

(19 citation statements)

References 93 publications

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“…An array of docking methodologies have emerged in the last few years, in response to a growing pharmacological interest for peptide-based drugs. Excellent reviews on such methods have been published ( Ciemny et al, 2016 ; Porter et al, 2019 ; Aderinwale et al, 2020 ), along with studies providing benchmark sets for assessing current and future methods. Here we provide an overview of the general principles behind these approaches as well as efforts from the simulation community in predicting protein-peptide interactions.…”

Section: Computational Methods Used To Study Protein-peptide Interactionsmentioning

confidence: 99%

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

Pérez

2021

Front. Mol. Biosci.

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Protein-protein interactions (PPIs) mediate a large number of important regulatory pathways. Their modulation represents an important strategy for discovering novel therapeutic agents. However, the features of PPI binding surfaces make the use of structure-based drug discovery methods very challenging. Among the diverse approaches used in the literature to tackle the problem, linear peptides have demonstrated to be a suitable methodology to discover PPI disruptors. Unfortunately, the poor pharmacokinetic properties of linear peptides prevent their direct use as drugs. However, they can be used as models to design enzyme resistant analogs including, cyclic peptides, peptide surrogates or peptidomimetics. Small molecules have a narrower set of targets they can bind to, but the screening technology based on virtual docking is robust and well tested, adding to the computational tools used to disrupt PPI. We review computational approaches used to understand and modulate PPI and highlight applications in a few case studies involved in physiological processes such as cell growth, apoptosis and intercellular communication.

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Section: Computational Methods Used To Study Protein-peptide Interactionsmentioning

confidence: 99%

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

Pérez

2021

Front. Mol. Biosci.

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“…To understand the physical mechanisms of these processes, determining the 3D structures of their associated protein complexes is a critical step. When protein complex structures have not yet been determined by experiment, it is possible to use computational tools to construct models of these complexes ( 1 ). A protein docking program can take two or more component protein structures as input and assemble them into atomic structure models of the protein complex.…”

Section: Introductionmentioning

confidence: 99%

LZerD webserver for pairwise and multiple protein–protein docking

Christoffer

Chen

Bharadwaj

et al. 2021

Nucleic Acids Research

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Protein complexes are involved in many important processes in living cells. To understand the mechanisms of these processes, it is necessary to solve the 3D structures of the protein complexes. When protein complex structures have not yet been determined by experiment, protein-protein docking tools can be used to computationally model the structures of these complexes. Here, we present a webserver which provides access to LZerD and Multi-LZerD protein docking tools. The protocol provided by the server have performed consistently among the top in the CAPRI blind evaluation. LZerD docks pairs of structures, while Multi-LZerD can dock three or more structures simultaneously. LZerD uses a soft protein surface representation with 3D Zernike descriptors and explores the binding pose space using geometric hashing. Multi-LZerD performs multi-chain docking by combining pairwise solutions by LZerD. Both methods output full-atom docked models of the input proteins. Users can also input distance constraints between interacting or non-interacting residues as well as residues that locate at the interface or far from the interface. The webserver is equipped with a user-friendly panel that visualizes the distribution and structures of binding poses of top scoring models. The LZerD webserver is available at https://lzerd.kiharalab.org.

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“…These guidelines are applicable also to other structural modelling-related studies, such as docking, binding and protein-protein interaction predictions (Aderinwale et al, 2020). Technical and other details and requirements discussed above are essential for understanding and evaluation of these studies, as well.…”

Section: Discussionmentioning

confidence: 99%

Guidelines for reporting protein modelling studies

Vihinen

2021

Preprint

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Computational modelling tools are widely used, however, articles describing modelling studies frequently do not contain sufficient details to allow the reader to comprehend the modelling procedure, quality of the produced model and validity of interpretations and predictions made based on the model. Here, guidelines were developed for items that have to be included when reporting studies and results based on protein modelling. A brief and concise checklist of required data items was compiled. These guidelines are simple to follow and apply, but require meticulous description of details, many of which can be placed to supplementary material. Authors have to pay attention to details when reporting modelling process. The generated structural models should be made publicly available, preferably by submitting to one of the existing repositories.

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Computational structure modeling for diverse categories of macromolecular interactions

Cited by 24 publications

References 93 publications

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

Computational Modeling as a Tool to Investigate PPI: From Drug Design to Tissue Engineering

LZerD webserver for pairwise and multiple protein–protein docking

Guidelines for reporting protein modelling studies

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